Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Over the weekend and during the R exams, I managed to complete the solution set for Chapters 6 and 7 of “Introducing Monte Carlo Methods with R”. Chapter 6 only exhibited a few typos, despite me covering most exercises in Chapter 6, hence the merging of both chapters.

– in Exercise 6.13, both $alpha$ and $beta$ must use a double exponential proposal in the Metropolis-Hastings algorithm of question b,

in Exercise 6.15, the $mathcal{L}(0,omega)$ distribution should be a $mathcal{N}(0,omega)$ normal distribution,

– in Example 7.3, part of the code is wrong: it should be

```> sigma2=theta=rep(0,Nsim)                  #init arrays
> sigma2=1/rgamma(1,shape=a,rate=b)      #init chains
> B=sigma2/(sigma2+n*tau2)
> theta=rnorm(1,m=B*theta0+(1-B)*xbar,sd=sqrt(tau2*B))```

```> sigma=theta=rep(0,Nsim)                  #init arrays
> sigma{1}=1/rgamma(1,shape=a,rate=b)      #init chains
> B=sigma2{1}/(sigma2{1}+n*tau2)
> theta{1}=rnorm(1,m=B*theta0+(1-B)*xbar,sd=sqrt(tau2*B))```

(I frankly don’t understand where those curly brackets came from!)

– in Example 7.6, I forgot to include the truncation probability $Phi(a-theta)^{n-m}$ in the likelihood (!) and the notations are not completely coherent with Example 5.13 and 5.14 in that the x’s became y’s…

– in Exercise 7.21, rtnorm is missing sigma as one of its arguments.

– Exercise 7.23 has nothing wrong per se but it is rather a formal (mathematical) exercise

– in Exercise 7.25 the $x+a$ in question a should be $(x+a)$ to avoid any confusion.

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